Aircraft Design in the 21st Century: Implications for Design Methods

Aircraft Design in the 21st Century: Implications for Design Methods Pradeep Raj, Ph.D. Technical Fellow Lockheed Martin Aeronautical Systems Marietta, GA

MAD Center Industrial Advisory Board Meeting Virginia Tech, Blacksburg, VA November 13, 1998

Scope

Aeronautical Systems Marietta, GA

A perspective on – Aircraft Industry Environment in the 21st Century – (Military) Aircraft Design Environment in the 21st Century – Implications for Methods Needed to Support Design (with CFD Slant) – Based on AIAA Paper 98-2895

The 20th Century


• Phenomenal Achievements in Aeronautics – From the Birth of Flight to Dominant Mode of Global Transportation – Integral Part of Any Credible National Defense Strategy

• Designs Driven by “Higher, Faster, Farther” Doctrine Continuous Improvements in Performance Accompanied by Continuous Increase in Complexity and Cost

The 21st Century


• Different Marketplace – Post-Cold War Geopolitical Considerations – “Globalization” of Commerce and Industry

• Affordability: Overarching Challenge – Customers Demand Higher Performance at Lower Costs! – Higher Performance at Still Higher Costs: No Longer the Right Paradigm

Technologically Superior Products and Services at Affordable Cost

Affordability Challenge PAST: Continuous Improvements in Performance Accompanied by Continuous Increase in Complexity and Cost


More than 50% Decline in DoD Procurement Budget over Five Years in Early 1990s! 120 100

$B

80 60 40 20 0 1989 1990 1991 1992 1993 1994 1995 1996

Factor of Four Increase Every Ten Years!

FUTURE: Technologically Superior Weapon Systems but Significantly Reduced Cost of Ownership

Response to Affordability Challenge • A Wide Range of Initiatives – Customer: Department of Defense – Suppliers: Aerospace Industry

• Three Examples – Consolidation – “Lean” Production – Simulation Based Acquisition


Consolidation


• U.S. Defense Industry – From 15 to 4! Grumman Westinghouse* Northrop

Northrop Grumman

1990

Raytheon

Texas Instruments* Raytheon* E-Systems GM Hughes*

Lockheed Martin Boeing

General Dynamics* Loral GE Aerospace Martin Marietta Lockheed

0

McDonnell Douglas Rockwell* Boeing *aerospace defense unit

1997

0

10

20

30

20

• •

40

Reduce Excess Capacity Reduce Overhead Costs

• U.S. Department of Defense – Reengineer Support and Infrastructure Area: 65% of Budget, 60% of People! • Base Realignment and Closure (BRAC) • Logistics Restructuring—Do More with Less

60

Lean Aircraft Initiative


• Established in 1993 – To Facilitate Transition of Lean Principles and Practices to Military Aircraft Industry

• Led Jointly by Industry and DoD – MIT is “Neutral Broker”

Improve All Aspects of Product Realization

“Lean” Production


• Industry Restructuring to Adopt “Lean” Practices – Inspired by “The Machine that Changed the World”

• Emphasis on Reducing Time to – Move a Product from Concept to Launch – Fulfill an Order After Receiving it from a Customer – Turn Raw Materials into Finished Products

• “Focus Factory” for Small Extrusions at LMAS – Throughput Time Down from 65 days to 12 days (Phase 1) and from 12 days to 158 seconds (Phase 2)

Eliminate Waste and Non-Value-Added Work

Simulation Based Acquisition: Key Element of DOD Response to Affordability Challenge

• Three Primary Goals – Substantially Reduce Time, Resources, and Risk – Increase Quality, Utility, and Supportability while Reducing Total Ownership Cost – Enable Integrated Product and Process Development (IPPD) Concept Across Full Acquisition Life Cycle

• Use of Modeling & Simulation Required – Integrated Across Acquisition Phases and Programs

Compress Time and Reduce Cost


Measure of Affordability


Life Cycle Cost (LCC) or “Cradle-to-Grave” Incurred Cost 60 50

Incurred Cost (%)

Incurred Cost (%)

50

40 30 30 20 20

10

0 Design & Test

Production

O&S

Production + Operation & Support Costs—80% of LCC!

Design and LCC


Design Activities Have Disproportionately Large Impact on LCC

Percentage of Life Cycle Cost

Program Calendar Time (Not to Scale)

A Large Amount of LCC−−more than 80%—is Committed in Early Stages of Design Unless Principal Objectives of Design Include Reducing Production and O&S Costs, Affordability Will Remain an Elusive Goal

Nature of Design


• An Iterative Decision-Making Activity • Success Depends on Quality and Timeliness of Decisions • On-time, Quality Decisions Depend Upon Availability of Quality Data at the Right Time • Many Methods Developed to Facilitate Decision-Making – Computer-Aided Design (CAD) – Finite Element Methods (FEM) – Computational Fluid Dynamics (CFD)

• BUT, Life Cycle Costs have Continued to Grow!! • Real Culprit: Traditional Design Practices – Evolved in an Era When Performance was Primary or Even the Only Consideration; Life Cycle Cost was a Fall Out – Long Cycle Time, High Risk

Traditional Design Process

• • •


Decisions Made in Early Stages Using Data from Crude and Simplistic Analyses Much Time Spent to Reconcile Design Changes Proposed by Various Disciplines Design, Manufacturing, Operations and Support Essentially Segregated

Long Cycle Time, High Risk

IPPD Design Paradigm • Integrated Approach


120

Knowledge about Designs

– Simultaneously Consider All 100 Aspects Including Design, % Manufacturing, and Support 80 – Consider All Requirements and 60 Constraints from Start – Reduce Need for Design Changes 40 in Later Stages – Perform Cost/Performance Trade20 offs Early Using More Knowledge

• Modern-Day Approach to Mimic Earlier Days of Design – Close Interaction through Integrated Teams, Methods and Tools – Effective Communications Through Information Technology – NOT “Automated Design”

------ Traditional —— IPPD Freedom to Change Designs

0

Conceptual

Preliminary

Detail

Shortens Design Cycle Time Reduces Risk

IPPD Design Environment


• Closer Relationship with Customer – Better Understand Customer Requirements

• Integrated Product Teams – More Complete Understanding of Requirements – Broader and Balanced Discussion of Alternatives – Simultaneous Design of Product and Process

• Design for X Methods – Design for Manufacturability, Producibility, Maintainability, Reliability, Safety, Quality, Cost, etc.

• Digital Product Model – Integrate Design and Analysis Tools to Capture and Refine Product and Process Data

• Integrated Design Automation Tools – Streamline Design Process and Assure Understanding of Design Intent

• Extensive Use of Physics-based Methods and Simulation Tools – For Improved Product Performance with Fewer Design/Build/Test Iterations

Design Methods


Create, Alter and Define Configuration Geometry

CAD

CA E

M CA

Model Fabrication, Tooling and Assembly Processes

Product Definition Database Produce Data for Quality, Performance and Reliability Assessment

Integration Using Product Definition Database Data From All Methods Must Conform to Database Standards Useable by Other Communities (Acquisition, Logistics, Operations, etc.)

CAD Methods


• Solid Models – – – –

Complete 3-D Models Including Geometry, Topology and Tolerances Easy to Understand and Interpret Enhance Communication of Design Intent Through More Realistic Visualization Enable More Effective Simulation of Assembly of Parts and Accessibility of Components

• Feature-Based Representation – Specify Features (Holes, Slots, Fillets, etc.) to Simplify Creation of Design – Include Attributes Such As Dimensions, Parameters and Tolerances as well as Cost, Process Requirements, and Producibility Constraints – Help Designer Think in terms of Manufacturing Cost, not just Geometry

• Parametric Design – Facilitate Generation of Multiple Parts or Assemblies by Varying a Few Parameters While Maintaining Overall Geometric Relationships – Minimize Time and Effort of Design Modification

CAM Methods


• Modeling of Manufacturing Processes – Layout of Production Equipment – Process Plans for Given Production Process – NC Programming for Parts and Subassembly – Tools and Fixture Design – Dimension and Tolerance Analysis – Factory Simulation – Ergonomics – Feature-Based Costing

• Simulation of Production System – Combine CAM and CAD Methods to Simulate Production System Prior to Physical Installation

Virtual Product Development Initiative LM Tactical Aircraft Systems, Fort Worth, TX

CAE Methods


• Configuration Analysis – Provide Data Needed to Assess Effectiveness of Designs and for Simulation of Performance – Minimize Need to Build and Test Physical Prototypes – Examples: CFD, FEM, CEM, etc.

• Multidisciplinary Interactions – Coupled CAE Methods for Predicting Multidisciplinary Interactions—A Cornerstone of IPPD Design – Example: CFD+CSM to Study Aeroelastic Interactions of a Flexible Aircraft

• Design Optimization – Computationally Define and/or Refine Geometric Shapes to Produce Desired Characteristics – Unique Ability to Generate Optimum Shapes – Combine CAE Methods with Numerical Optimizers

Pivotal Role of CFD


• Key Modeling & Simulation Technology for Airframe Design and Development – Product Upgrade • Evaluation of Design Modifications to Integrate New Components/Subsystems

– New Products • Aerodynamic Shape Optimization • Multidisciplinary Design Optimization

• Crucial for Successful Implementation of IPPD Design Paradigm – Ensure that Required Mission and Cost Targets Can be Met • • • •

Airplane Performance Assessment: Cruise and Maneuver Flight Conditions Structural Design: Steady and Unsteady Flight Loads Flight Control System Design: Rate Derivatives Design Optimization: Sensitivity of Aerodynamic Data to Design Variables

Numerous CFD Analyses: An Integral Part of Future Design Process

CFD Current Capability


• Effectiveness: The Right Measure of Merit for CFD – Ability to Meet Desires and Expectations of Designers

• Components of Effectiveness* Effectiveness = Quality x Acceptance

• Quality Factor – Credible Data (Accuracy)

Four Levels with Varying Degrees of Effectiveness

• Acceptance Factors – Timeliness (Turnaround Time) –

Cost (Labor and Computer)

*Adapted from L.R. Miranda, Journal of Aircraft, June 1984, pp. 355-370

CFD Principal Challenges


• Reduce Analysis CYCLE TIME – Reduce Total Turnaround Time From Go-ahead to Data Delivery

• Produce Data of RELIABLE ACCURACY – Increase Level of Confidence in Results

• Decrease COST of Generating CFD Data – Minimize Labor + Computer Expenses

Need Dramatic Improvements in Effectiveness

CFD Turnaround Time • Minimize Calendar Time: Top Priority • No Single Target Value – Depends on Scope – Customer Needs

• Three-Step Process – 1. Acquire Geometry and Generate Grid – 2. Run Flow Solver – 3. Extract Engineering Data from Flow Solver Output

Apply Lean Principles to Eliminate Waste


CFD Turnaround Time


• Step 1: Geometry Acquisition and Grid Generation – Eliminate Non-Value-Added CAD Geometry Clean-up – Implement Fully Automated Grid Generation • Cartesian? Hybrid?

– Eliminate Manual Rework to Improve Grid Quality • Adaption?

If a Lean Process Cannot be Developed Using Existing Technologies, Need to Explore Alternative Enabling Technologies

CFD Turnaround Time


• Step 2: Running Flow Solver – – – – –

High-performance Computing for Run Times on the Order of Minutes More Efficient Algorithms—Especially for Unsteady Flows Convergence Acceleration Smaller Computational Domains Increased Robustness: One Run, One Solution!

• Step 3: Extracting Engineering Data – – – –

Less Manual, More Automated Data Analysis and Visualization Improved Man/Machine Interface Standard Data Exchange Protocols Intelligent Data Management

Maximum Efficiency of the Entire Analysis Process

CFD Accuracy


• Credible Data – Full Aircraft Geometries and Entire Speed, Altitude, and Maneuver Flight Envelope

• Known and Acceptable Error Bounds – Critical For Multidisciplinary Design Optimization (MDO)

• Two Main Sources of Error – Numerical Modeling – Physical Modeling

MAD Center Report 96-06-01, Virginia Tech, Blacksburg, VA

CFD: Numerical Accuracy


• Extensive Parametric Studies to Minimize Numerical Errors – NOT Suited for IPPD Design Environment; Takes Too Long

• Reliance on Past Experience – Too Risky: • Different Configurations, Different People, Different Methodology • Extensive, Detailed Case Histories Successes & FailuresNot Available

• What is Needed? – Minimum Sensitivity to Grids and Numerical Parameters – Built-in Means of Quantifying Level of Errors

M = 0.4

CFD: Physical Accuracy


• How Well Predictions Stack Up Against Reality • Traditional Code Validation Does Not Increase Credibility – Monumental Task • How Many Test Cases? Flow Conditions? Turbulence Models?

– Never Ending Process • Codes May Change Even Before Task Finishes

– More Data Than Knowledge for Design Efforts – Military Aircraft: Vastly Different Designs

• Focus Instead on “Standard” Benchmark Test Cases – Code Developers to Perform Comprehensive Parametric Studies – Provide Guidelines for Acceptable Levels of Accuracy for Common Types of Flow (Boundary Layers, Shear Flows, Vortex Flows) – Provide Sound Basis for Code Comparisons

• Follow DoD VV&A Procedures for Design Activities • Transition/Turbulence Modeling−−Insurmountable Hurdle for RANS?

CFD Cost


• Labor Expenses – Reducing Turnaround Time Reduces Labor Expenses

• Computing Expenses – Expensive Computers with Large Memory and High Processing Speed Needed to Produce Desired Amounts of Data – IPPD Design Requires Full Range of Data in Days, Not Months – Answer: Low-Cost Computing?

• Engineering Productivity Issues – Low-Cost Computing Will Reduce Visible Costs, BUT Invisible Costs May Increase if Computing Times Increase Significantly • Delays in Decision Making • Wasted User’s Time in Waiting for Solutions

– Must Trade-off Visible Costs of Hardware/Software Systems and Invisible Costs of Productivity Loss for Maximum Effectiveness

Concluding Remarks


• The Affordability Challenge – Provide Technological Superiority at Affordable Cost – Particularly Acute for Military Aircraft

• IPPD Design Environment – Reduce Design Cycle Time – Lower Design Risk – Relies on Quality Data for More Informed Decisions in Early Stages of Design

• Pivotal Role of CFD – Product Upgrade – New Products • Aerodynamic Shape Optimization • Multidisciplinary Design Optimization

• Maximize CFD Effectiveness – Rapid Turnaround – Reliable Accuracy – Lower Cost